no code implementations • 31 Jan 2019 • K. Kawagoe, Y. Miura, I. Sekiya, T. Suehara, T. Yoshioka, S. Bilokin, J. Bonis, P. Cornebise, A. Gallas, A. Irles, R. Pöschl, F. Richard, A. Thiebault, D. Zerwas, M. Anduze, V. Balagura, V. Boudry, J-C. Brient, E. Edy, G. Fayolle, M. Frotin, F. Gastaldi, R. Guillaumat, A. Lobanov, M. Louzir, F. Magniette, J. Nanni, M. Rubio-Roy, K. Shpak, H. Videau, D. Yu, S. Callier, F. Dulucq, Ch. de la Taille, N. Seguin-Moreau, J. E. Augustin, R. Cornat, J. David, P. Ghislain, D. Lacour, L. Lavergne, J. M. Parraud, J. -S. Chai, D. Jeans h
The technological prototype of the CALICE highly granular silicon-tungsten electromagnetic calorimeter (SiW-ECAL) tested in beam at DESY in 2017.
Instrumentation and Detectors
no code implementations • 11 Oct 2018 • S. Bilokin, J. Bonis, P. Cornebise, A. Gallas, A. Irles, R. Pöschl, F. Richard, A. Thiebault, D. Zerwas, M. Anduze, V. Balagura, V. Boudry, J-C. Brient, E. Edy, G. Fayolle, M. Frotin, F. Gastaldi, A. Lobanov, F. Magniette, J. Nanni, M. Rubio-Roy, K. Shpak, H. Videau, D. Yu, S. Callier, F. Dulucq, Ch. de la Taille, N. Seguin-Moreau, J. E. Augustin, R. Cornat, J. David, P. Ghislain, D. Lacour, L. Lavergne, J. M. Parraud, K. Kawagoe, Y. Miura, I. Sekiya, T. Suehara, H. Yamashiro, T. Yoshioka, D. Jeans, J. -S. Chai
In this article we describe the commissioning and a first analysis of the the beam test performance of a small prototype of a highly granular silicon tungsten calorimeter.
Instrumentation and Detectors
no code implementations • 17 Oct 2016 • W. Xiong, J. Droppo, X. Huang, F. Seide, M. Seltzer, A. Stolcke, D. Yu, G. Zweig
Conversational speech recognition has served as a flagship speech recognition task since the release of the Switchboard corpus in the 1990s.
Ranked #4 on Speech Recognition on Switchboard + Hub500
no code implementations • 12 Sep 2016 • W. Xiong, J. Droppo, X. Huang, F. Seide, M. Seltzer, A. Stolcke, D. Yu, G. Zweig
We describe Microsoft's conversational speech recognition system, in which we combine recent developments in neural-network-based acoustic and language modeling to advance the state of the art on the Switchboard recognition task.
Ranked #4 on Speech Recognition on swb_hub_500 WER fullSWBCH